Course Title: Advanced SQL for Data Management & Optimization

📅 Duration: 4 Weeks (Twice a Week)
🖥 Format: Online Live Sessions + Hands-on Assignments

Week 1: Query Optimization & Indexing

📌 Session 1:

• Understanding Query Execution Plans (EXPLAIN & EXPLAIN ANALYZE)

• Identifying and Fixing Slow Queries

• Using Indexes (BTREE, HASH, GIN, GIST) for Performance Boost

• Mini Project: Optimizing Queries for a Large Dataset

📌 Session 2:

• Creating and Managing Composite & Partial Indexes

• Using Materialized Views for Faster Data Retrieval

• Caching Strategies for SQL Queries

• Mini Project: Performance-Tuned Reporting Dashboard

Week 2: Advanced Joins, Subqueries & Window Functions

📌 Session 3:

• Recursive Queries with Common Table Expressions (CTEs)

• Advanced Joins (CROSS JOIN, SELF JOIN, LATERAL JOIN)

• Using Pivot & Unpivot Queries for Data Reshaping

• Mini Project: Complex Data Aggregation for Business Analytics

📌 Session 4:

• Deep Dive into Window Functions (RANK(), DENSE_RANK(), LEAD(), LAG())

• Using Partitions for Efficient Query Processing

• Moving Averages and Running Totals with Window Functions

• Mini Project: Trend Analysis Using Window Functions

Week 3: Stored Procedures, Functions & Transactions

📌 Session 5:

• Writing and Executing Stored Procedures

• Creating Custom SQL Functions for Business Logic

• Handling Errors in Stored Procedures (TRY…CATCH, RAISE EXCEPTION)

• Mini Project: Automated Data Processing with Stored Procedures

📌 Session 6:

• Advanced Transaction Management (SAVEPOINT, ROLLBACK TO SAVEPOINT)

• Implementing ACID Principles in Real-World Databases

• Understanding Isolation Levels & Concurrency Control

• Mini Project: Banking System Transaction Management

Week 4: Security, Big Data & Final Project

📌 Session 7:

• Advanced User Management & Role-Based Access Control (GRANT, REVOKE)

• Protecting Against SQL Injection & Data Leaks

• Encrypting Data in SQL Databases

• Mini Project: Secure Database for User Authentication

📌 Session 8:

• Working with Big Data in SQL (Partitioning, Sharding, Parallel Query Execution)

• Integrating SQL with NoSQL (Hybrid Databases)

• Final Project Presentation & Code Review

• Next Steps: Data Engineering, Cloud Databases, or Advanced Analytics